code: def _get_interface_of_single_tensor(tensor):
      """Returns the name of the package that any array/tensor manipulations
      will dispatch to. The returned strings correspond to those used for PennyLane
      :doc:`interfaces </introduction/interfaces>`.
  
      Args:
          tensor (tensor_like): tensor input
  
      Returns:
          str: name of the interface
  
      **Example**
  
      >>> x = torch.tensor([1., 2.])
      >>> get_interface(x)
      'torch'
      >>> from pennylane import numpy as np
      >>> x = np.array([4, 5], requires_grad=True)
      >>> get_interface(x)
      'autograd'
      """
      namespace = tensor.__class__.__module__.split(".")[0]
  
      if namespace in ("pennylane", "autograd"):
          return "autograd"
  
      res = ar.infer_backend(tensor)
  
      if res == "builtins":
          return "numpy"
  
      return res
  
file_path: pennylane/pennylane/math/utils.py
imports: import warnings
  import autoray
  import numpy
  from autograd.numpy.numpy_boxes import ArrayBox
  from autoray import numpy
  from .None import single_dispatch
label_desc: Use image node_id 7 for calling a global function with example usage: _get_interface_of_single_tensor(tensor) and returns: res, str, str